1. Field
The methods and systems relate generally to signal and image data processing, and more particularly to improved detection in signal and image processing.
2. Description of Relevant Art
The separation of signal and noise can be understood as a fundamental issue in signal processing. Image processing is a well-known application of signal processing. Synthetic Aperture Radar (SAR) is one application that utilizes signal and image processing. In SAR applications, a Radar system that can be incorporated into an aircraft, for example, can be directed to regions on the earth""s surface to provide coherent phase history data, or in-phase and quadrature signal data, that can be processed to provide an image of the regions. This process can often be referred to as mapping. In SAR applications, a region can be mapped at various time intervals depending on the application. For example, SAR mappings can be used to detect changes in position of vehicles or other changes such as the alteration of a structure, vehicles, natural resources, etc. Signal and image data comparison can be a significant aspect in detecting a change between two mappings of the same or similar regions. Generally, methods and systems for comparing image data can include a coherent (i.e., phase and magnitude) and/or non-coherent (i.e., magnitude only) differencing between the image data of two mappings to be compared. A problem with these comparison systems is that, for applications such as SAR that utilize a coherent sensor, the comparison does not compensate for phase differences that can be caused by the sensor. For example, in an illustrative SAR application, phase changes between successive mappings can be caused by different viewing geometries, and systems and methods can fail to compensate for such phase changes.
The methods and systems described herein allow the comparison of two data signals. The first data signal can be applied to a first filter, and the second data signal can be applied to a second filter. The first and second filters can be constrained according to minimize the energy difference between the filtered first data signal and the filtered second data signal. The filters can also be constrained according to a first model response and a second model response, respectively. In one embodiment, the first model response can include unity magnitude and zero phase, while the second model response can include unity magnitude and variable phase.
In one embodiment, the mean energy between the filtered signals can be computed. Furthermore, the minimization can occur based on phase angle.
The energy difference can be computed on a frequency basis and compared to a threshold that can be fixed or adapted. The frequencies satisfying the threshold can be understood to represent differences between the signals.
The energy difference computation can include compensation terms that can be additive to the energy difference computation. In one embodiment, the additive term can include two additive components that include a first multiplier multiplied by a squared Euclidean norm based on the first filter, and a second multiplier multiplied by a squared Euclidean norm based on the second filter.
In an embodiment, the methods and systems can be applied to data from a coherent sensor that can be Synthetic Aperture Radar (SAR), acoustic data, seismic data, etc. The data can be provided in vectors of length N and processed in segments of length M, where N and M can be positive integers and M can be less than or equal to N.
Other objects and advantages will become apparent hereinafter in view of the specification and drawings.